A light generator is a device used to generate various types of lighting conditions for various applications that may require a particular brightness, spectrum or other characteristic of light. Light generators may be used in a variety of applications including, but not limited to, evaluation and processing of light sensitive products, controlling photochemical reactions with high accuracy and versatility and colour testing.
One particular application of a light generator is as a solar simulator, which is a device used to simulate solar radiation. While much of the following discussion relates to solar simulators, it will be understood that at least some of the principles and improvements described will apply to other light generator applications.
Solar simulators may be used in a variety of applications including, but not limited to, determining the response of a device or object when exposed to sunlight. Solar simulators allow this testing to be performed at will in a controlled and reproducible fashion.
A common application of a solar simulator is performance testing and classification of photovoltaic (“PV”) cells and modules. In this application, the basic requirement of the solar simulator is to provide a fair approximation of sunlight so that performance of PV devices can be qualified and the outdoor performance of modules can be estimated from indoor production metrology. Such testing is useful during photovoltaic design and fabrication activities, as well as quality assurance in the factory and field. An advantage of a simulator is that the simulator may provide a reproducible set of conditions for obtaining performance measurements. It is important to be able to determine and optimize cell performance prior to field installation, as well as in-field testing.
Other applications of a solar simulator include performance testing and production quality control of sun-block or other Ultra-Violet (UV) protective products, measuring weatherability and fade resistance of materials, quality assurance for color matching of paint finishes, and performance testing of outdoor signs and other products that are generally used outdoors where cosmetic features are important. In these applications, spectral match with real sunlight over the entire spectrum may not be necessary. In accelerating lifetime testing intensity in excess of typical solar irradiation may be required.
Solar simulators generally consist of a source or sources to generate the light, delivery optics to direct the light and related drivers and controls. The design of the delivery optics influences the divergence and uniformity of the light over a target, such as a PV module or the like.
The prototypical source is a short arc xenon lamp. There are also alternatives to the xenon lamp, including mercury, mercury-xenon, quartz halogen lamps, metal halide and tungsten lamps. Conventional solar simulators using lamps can have a number of limitations or difficulties that are well documented in the literature, including: poor spectral match with nominal solar spectra, capability, stability, versatility, cost, and size.
More recently, solid state emitters have gained some attention with regard to solar simulators. While some improvements seem to have been made, current academic and known solar simulators using solid state emitters continue to have limitations or difficulties with regard to poor spectral matching, consistency of brightness, versatility of testing applications, complexity of control systems, and the like. A lack of versatility can severely limit what measurements (methods, systems, and applications) individual solar simulators can accomplish and can also limit their cost compared to their benefit.
In order to better understand the limitations of existing solar simulators, it is useful to understand the basics of solar radiation and current standards for solar simulators, and in particular, to standards relating to solar simulators for use with photovoltaic (PV) cells or modules (solar cells or modules).
The sun is, approximately, an incandescent source with a coordinated color temperature (CCT) of ˜5600° K. The resulting spectrum spans from ultraviolet to infra-red (IR). Sunlight is filtered by the solar and the Earth's atmospheres with some strong absorption bands presented by the Earth's atmosphere. The resulting spectrum is therefore highly structured, and covers the ultraviolet to infra-red. A ‘Standard’ spectral power distribution for sunlight, known as air mass 1.5 global radiation or AM1.5G, is codified in the standard ASTM G173-03. This is a data set, which represents idealized sunlight under average atmospheric conditions for the continental USA at the average latitude of the continental USA at sea level (including direct and indirect radiation). It further assumes irradiance on a surface tilted towards the sun at noon at latitude where the total air mass in the path of the sunlight is 1.5 times the air mass (“AM”) straight overhead. This defines a nominal spectral irradiance against which solar simulators may be judged. There are other possible standards that could be applied in certain cases such as AM00—extraterrestrial radiation—and AM 1.5D—direct radiation only. It is typically the goal of a full spectrum solar simulator to provide a reasonable replica of this irradiation. Note that this standard irradiance (AM1.5G) includes direct sunlight with a subtended angle of ˜0.53 degrees and diffuse sunlight, which has a much broader subtended angle, affected by atmospheric conditions, but is mostly contained within ˜15 degrees.
A standard level of noon-time solar irradiance, generally referred to as ‘1 sun’, assuming the AM1.5 atmospheric condition is taken to be 1 kW/m2 although this is somewhat arbitrary as the ASTM standard provides a value which is slightly less and may be approximately 0.995. By convention, average solar irradiation at top of atmosphere is taken to have an irradiance of 1366 W/m2, although satellite observations average closer to 1362 W/m2 (which would change the ASTM model). In any case, the exact value would vary somewhat at different times of the year due to eccentricities in the terrestrial orbit with longer term cyclic variations.
The existing standards for photovoltaic solar simulators (e.g. IEC 60904-9, ASTM E927-05, JIS C 8912) divide the standard spectrum into six wavelength bands, and consider only the proportion of power within each band, with no concern of how spectral power is distributed within a band. The simulators are then classified in terms of how well their output compares to standard sunlight according to three criteria: spectral match, uniformity of intensity over the output area, and stability with time. Classifications include A, B and C, A being the best generally for spectral match, spatial uniformity and stability. Spectral class limits A, B & C are further discussed below. Directionality and out of-band irradiation levels are not specified.
TABLE 1Classification Standards of Solar SimulatorsOrganizationASTMIECJISStandardE927-0560904-9C 8912ClassABCABCABCSpectral match0.750.600.400.750.600.400.750.600.40(low/high)1.251.402.001.251.402.001.251.402.00Irradiation351025102310uniformity (±%)Short term———0.5210———stability (±%)Temporal stability (±%)251025101310
Solar simulators are typically expected to produce a nominal irradiance of approximately 1 kW/m2; however, performance testing for other conditions such as equatorial (AM1.0) or high elevation or extraterrestrial conditions may require as much as 37% greater irradiance. Similarly, accelerated lifetime testing and light soaking applications will often require higher irradiance. Low light level performance may also be of interest, particularly when testing photovoltaic or solar thermal devices. The noted standards do not fully address this issue nor do conventional solar simulators allow for these additional types of testing.
In the context of PV devices, the most commonly measured parameters are related to the PV device's electrical characteristics (so called current versus voltage (“IV”) curve) under one or more light levels and a prediction of the PV device's power production capability. In a PV testing environment, reference cells play an important part by providing a means to accurately quantify the light output from the solar simulator, and calibrate the testing system. Traceable reference cells calibrated to a standard solar spectrum are generally supplied by recognized test labs such as NIST.
Currently, solar simulators are typically used to measure photoelectrical conversion efficiency and possibly some other properties in two or three places in the production process of photovoltaic cells and modules: cell testing & sorting (after metallization), cell string testing (after tabbing and stringing and during bussing and layup, TF module after back-contact formation), module testing and certification (after final assembly). There may be other opportunities to apply solar simulators in the manufacturing process; however, this is not generally done, possibly due to the cost and bulk of conventional solar simulators.
There are various platforms of photovoltaic cell technologies in the market place, such as mono and poly-crystalline silicon and amorphous silicon, thin film arrays, Ge and GaAs based multi-junction, CdTe, CIS, CIGS, concentration strategies, as well as several emerging technologies. Each of these platform technologies has different optical and electrical properties, and, as such, a different set of requirements with regard to how to test with an equivalent of standard sunlight. These differences are generally not easily handled by conventional solar simulators and are also generally not reflected in current standards for solar simulator performance.
A study of European test labs showed that state of the art reproducibility was no better than ±2.5% for conventional (Si) devices. Photometric accuracy, which is not addressed in the previous standards, should also be required. A recent inter-comparison of recognized test lab results showed power ratings for mono-Si, a-Si, and CIS modules deviated by 7.4%, 16.9%, and 11.6%, respectively. ISO considers “Lack of Performance Data” & “Uncertainty in Module Performance Ratings” to be barriers to adoption of PV, referring to the current uncertainty in ratings estimated to be +/−6%. These are enormous uncertainties to be introduced into large-scale commercial ventures such as large-scale solar farms, which can exceed $1 B in capitalization. Issues of non-reproducibility have at least two kinds of impact: the ability to research, develop and optimize technologies and processes depends on the precision of the available metrology; the ability to accurately predict performance is a substantial commercial issue since product selling price is largely tied to power ratings of the devices.
There have been several formal studies into this area. The EC ‘Performance’ project is conducting extensive studies including two consecutive round robin inter-comparisons where solar simulators results from several test labs are being compared—the end goal being reproducibility of +/−1% while initial results showed −2/+3%. These results are obtained after normalizing the results to an outdoor reference and consequently, do not represent the total spread in data that might be seen in convention practice with production line meteorology Also, these results were obtained using primarily c-Si PV modules and averaging results, where this is the least problematic PV technology to measure. In a related project ‘PC-Catapult’ a similar round robin trial was performed—in this case, sources of variability were examined using formal gage capability studies revealing measurement uncertainty a large as 7% (Pmax) based on module type and 8% based on simulator model. Another EC project ‘Crystal Clear’ performed similar studies. Photon Labs, produces an annual comparison of real world module performance to ratings which also shows a substantial spread, +6.3/−3.9%, which has significant commercial implications and can, at least in part, be attributed to problems with in-house metrology and/or lack of agreement between test labs. The general conclusion from this information was that there is room for improvement.
Of note, test labs that are responsible for certifying PV modules, providing reference cells and qualified cell and module sample sets, are currently reduced to using the same or similar devices as manufacturers. The same may be said for research labs and other technology developers and for Q/A metrology in the industry. This is at variance with the rule of thumb that metrology should have a precision to tolerance ratio (P/T) of <0.33 for production management, <0.20 for process control and <0.1 for quality assurance and <0.01 for standards. This would imply a structured regime where devices with performance ranging from fair to good to excellent are available on the market. This is currently not the case.
Based on the above issues and difficulties with conventional solar simulators, there is a need for improved light generators that can be used as solar simulators and in other applications.